
where \(\mathbf {X}\)  is the regularly sampled grid within the object bounding box and \(d\)  is the depth step size used in the coarse NeRF sampling.
Translation and scale canonicalization is simply achieved by moving the bounding box's center [1]} and scaling it, so our next concern is on rotation canonicalization.
